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. 2012 Feb 28;6(2):1648-56.
doi: 10.1021/nn204631x. Epub 2012 Jan 18.

Controlling Self-Assembly of Engineered Peptides on Graphite by Rational Mutation

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Free PMC article

Controlling Self-Assembly of Engineered Peptides on Graphite by Rational Mutation

Christopher R So et al. ACS Nano. .
Free PMC article

Abstract

Self-assembly of proteins on surfaces is utilized in many fields to integrate intricate biological structures and diverse functions with engineered materials. Controlling proteins at bio-solid interfaces relies on establishing key correlations between their primary sequences and resulting spatial organizations on substrates. Protein self-assembly, however, remains an engineering challenge. As a novel approach, we demonstrate here that short dodecapeptides selected by phage display are capable of self-assembly on graphite and form long-range-ordered biomolecular nanostructures. Using atomic force microscopy and contact angle studies, we identify three amino acid domains along the primary sequence that steer peptide ordering and lead to nanostructures with uniformly displayed residues. The peptides are further engineered via simple mutations to control fundamental interfacial processes, including initial binding, surface aggregation and growth kinetics, and intermolecular interactions. Tailoring short peptides via their primary sequence offers versatile control over molecular self-assembly, resulting in well-defined surface properties essential in building engineered, chemically rich, bio-solid interfaces.

Figures

Figure 1
Figure 1
Chemical properties of GrBP5 sequence and its self-assembled, ordered, nanostructure on graphite (0001) lattice. (a) The three chemically distinct domains of GrBP5. The mean hydropathy (defined by Kyte and Doolittle) value of Domain-I is 3.53 (on an increasing scale from -4.5 to 4.5) and -1.86 for Domain-II, making the latter considerably more hydrophilic. (b) AFM image of GrBP5 on graphite showing ordering of the WT peptide over several micrometers displaying six-fold symmetrical self-assembled nanostructures, as observed in (c) the FFT of the AFM image.
Figure 2
Figure 2
Time-lapsed AFM of GrBP5 assembly. (a) Height contrast AFM images, for 10, 60 and 180 minutes, display structural evolution beginning with (left) discrete peptide clusters; (middle) growth of both amorphous (AP), and ordered (OP) phases as respectively labeled; and (right) complete OP monolayer. (b) Psuedo-3D representations of boxed regions showing height contrast among the phases formed: discrete (red), higher AP (yellow) and flat OP (orange), which are labeled below (c) on cross- sections of height taken across *---* in (a). Inset (d) shows lateral growth of OP including a cross sectional height taken between two peaks of AP peptides on either side. (e) Plot of percent total disordered/ordered peptide vs total coverage showing ordering transition and (f) Schematic of peptide self-assembly process highlighting surface phenomena: (i) Aggregation involving binding, diffusion, and clustering processes and (ii) Ordering involving self-assembly.
Figure 3
Figure 3
Time-lapse behavior of the peptides with Domain-III mutations. (a) In Mutant 1 the aromatic residues, Tyrosine (Y), of GrBP5 are eliminated and replaced by Alanine (A) resulting in no bound molecules on surface. (b) Tryptophan and (c) Phenylalanine replace WT-Tyrosine in Mutants 2 (M2) and 3 (M3), respectively. The resultant peptides, respectively, are either strongly bound to the surface forming percolated, but finely porous, film (M3) or weakly bound peptides forming isolated islands, each over the course of 3 hours. (d) Fractional coverage trends from time-lapse AFM of WT, M1, M2, and M3; (e) Particle count of each of the peptides; and (f) Average particle size over time; Error bars represent standard deviation of 3 different images from the sample surface, totaling an area of 16 μm2.
Figure 4
Figure 4
Quantification of graphite affinity for aromatic mutants. (a) AFM images of HOPG exposed to 0.5 and 5.0 μM of WT, M1, M2, and M3 peptides for 3 hours. (b) Graph of surface coverage for each peptide plotted against concentration, and fitted using a Langmuir adsorption model for affinity constant, K. Error bars represent standard deviation of 3 different images from the sample surface, totaling an area of 16 μm2.
Figure 5
Figure 5
Chemical properties of Domain-I mutants and their assembly behavior. (Left column) Domain-I mutant sequences and hydropathy values; (Right column) AFM images of hydropathic mutants on HOPG, and (insets) contact angle measurements of imaged surfaces. (a) WT GrBP5 forms long-range ordered nanometer-scale structure and a high contact angle, θCA, of 65.3°. (b) Hydrophilic mutant M4 does not form an observable long range order and displays a low contact angle of 34.7°; while (c) Hydrophobic mutant M5 forms an ordered peptide film, similar to that of WT, with a much greater θCA of 88.9°.
Figure 6
Figure 6
Behavior of peptides during molecular self-assembly. (a) AFM height (red) and cosine of contact angle, cos(θCA), (blue) both plotted against surface coverage, respectively. Data from AP and OP images labeled accordingly. Blue dotted lines represent guides for the AP of peptides to demonstrate their shared linear behavior, i.e., chemistry, as defined by Cassie’s Law. Black arrow in WT indicates heights averaged from an image containing both AP and OP. Horizontal error bars represents standard deviation from 3 different analyzed images on the sample surface, totaling an area of 16 μm2. Vertical error bars are the standard deviation from two droplets on duplicate samples (b) A schematic of WT and M5 self-assembly mechanism where peptides undergo binding and diffusion via Domain-III, first aggregating randomly to form rough AP and, finally, rearranging Domains-I and -II while folding into OP. (c) Mechanism of M4 in the absence of hydrophobic Domain-I; here there is neither retraction in height nor change in surface chemistry.

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